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Hello dear Sir,
and thanks for sharing the code. I have some questions about the code. There are some lines that are not so clear like
num_examples = 1000 # number of examples per image to use for training model
Why do you take just 1000, what does this number represents? Which examples?
What are h_neigh and h_ind ? which role they play here?
h_ind = int((h_neigh - 1)/ 2)
label = label[h_ind:-h_ind, h_ind:-h_ind]
Why do you use patch (11,11)? You can also direct process the whole image?
cal_haralick gives back 13 features. Why do you take just the first 9 and leave the rest?
Why does the border is increased here ?
img = cv2.copyMakeBorder(img, top=border, bottom=border, \
left=border, right=border, \
borderType = cv2.BORDER_CONSTANT, \
value=[0, 0, 0])
Thanks
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